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Understanding the brain's electrical activity provides objective evidence of different psychophysical phenomena related to manual handling tasks. The primary objective of this research was to assess the neural signatures of human physical efforts and perceived comfort in isometric arm exertions. Two experiments were conducted with male participants (n=20) who applied isometric forces at 1) different levels of exertion and 2) different levels of physical comfort. EEG signals, the rate of perceived exertion (RPE), and the rate of perceived physical comfort (RPC) have been recorded. The results showed statistically significant differences in EEG's power spectral density (PSD) at different brain regions for different levels of physical exertion and comfort. Furthermore, different EEG bands were correlated with the applied forces and their perceptions. It was also found that during isometric arm exertions, different parts of the brain worked synchronously.

Extended reality (XR) can be a useful tool in the battlefield, provided it can perform at least as well as current technology used by the warfighter. The Multi-Domain Operations (MDO) framework, in which many military domains must informationally coordinate, necessitates a move toward technologies capable of delivering vital communications while maintaining situation awareness (SA). In the present work, a novel XR technology (Microsoft HoloLens 2) is compared with a traditional technology (tablet). Prior to administering the study, participants were given structured training in the use of the XR system, as well as in military symbology, units, and scenarios. Thereafter, in the experimental portion of the study, participants separately used two technologies, HoloLens 2 and a tablet. Their task was to understand military scenarios, and performance was assessed for SA, workload as measured by the NASA-Task Load Index (NASA-TLX), and usability as measured by the System Usability Scale (SUS). Within the HoloLens conditions, we measured the impact of displaying units on maps using symbology only or symbology with 3D models. Notably, in contrast to previous studies, results showed SA levels were not significantly different between technologies, and that SA scores were significantly higher for individuals with high training performance. We also saw significant differences in usability, such that the tablet outperformed the HoloLens 2, and the tablet scored lower in terms of workload. On the HoloLens, symbology-only maps were outperformed by symbology and 3D models maps, but only for SA level 3. These findings support the idea that XR technology can be helped by sufficient training to perform alongside more traditional technologies, while identifying a need for design improvements targeting workload and usability before the technology is ready to support MDO efforts, and warfighter.

Software development projects fail far too often, costing companies billions in revenue, loss of the intended purpose and damage to both customers and suppliers in the process (A. Shenhar & V. Holzmann, 2017a). Understanding the challenge of ever-failing globally distributed software development projects is the goal and research conducted in this dissertation. The vision guiding the direction of this research is "What are the betweenteam barriers that impede the successful delivery of Agile software development in Globally Distributed Teams?" Through the literature review, a model was created and refined. A Mixed-Method Sequentially Replicated Case Study Research was performed to determine within-case and cross-case findings. The research covers five replicated cases from various industries, including Food & Beverage, Oil & Gas, Insurance, and Healthcare. Using a Thematic Analysis process, the project leadership was questioned and interviewed. The results of the qualitative research were compared and contrasted with Likert data collected from the team members. Analysis performed included significant qualitative findings, most impactful factors, and alignment between the leaders and team members. The research found that all factors can be vital enough to cause a project to fail. The research found that the process factor is significantly less impactful than initially thought, and the people (the team) factor are clear success criterion. The research provides value to current and future project owners by providing them with criteria to evaluate their projects. The evaluation against criteria allows a project owner to adjust or create the conditions for success. Future research should be capable of expanding on this research by creating practical guides and specific tools for project creation where the projects have a greater success rate.

Functional magnetic resonance imaging (fMRI) is a non-invasive technology that provides high spatial resolution in determining the human brain's responses and measures regional brain activity through metabolic changes in blood oxygen consumption associated with neural activity. Task fMRI provides an opportunity to analyze the working mechanisms of the human brain during specific task performance. Over the past several years, a variety of computational methods have been proposed to decode task fMRI data that can identify brain regions associated with different task stimulations. Despite the advances made by these methods, several limitations exist due to graph representations and graph embeddings transferred from task fMRI signals. In the present study, we proposed an end-to-end graph convolutional network by combining the convolutional neural network with graph representation, with three convolutional layers to classify task fMRI data from the Human Connectome Project (302 participants, 22–35 years of age). One goal of this dissertation was to improve classification performance. We applied four of the most widely used node embedding algorithms—NetMF, RandNE, Node2Vec, and Walklets—to automatically extract the structural properties of the nodes in the brain functional graph, then evaluated the performance of the classification model. The empirical results indicated that the proposed GCN framework accurately identified the brain's state in task fMRI data and achieved comparable macro F1 scores of 0.978 and 0.976 with the NetMF and RandNE embedding methods, respectively. Another goal of the dissertation was to assess the effects of individual differences (i.e., gender and fluid intelligence) on classification performance. We tested the proposed GCN framework on sub-datasets divided according to gender and fluid intelligence. Experimental results indicated significant differences in the classification predictions of gender, but not high/low fluid intelligence fMRI data. Our experiments yielded promising results and demonstrated the superior ability of our GCN in modeling task fMRI data.

The purpose of the quantitative non-experimental research study is to analyze the relationship between the impact of using cost engineering approaches and the success rate of Six Sigma projects in the manufacturing industry. This study focuses on the relationship between Six Sigma project failures and whether skilled cost engineering professionals, methods or a cost management system was used to ensure that accurate cost data was utilized during the design project's lifecycle. Many companies using Six Sigma and related methodologies for product design have implemented with great success yet there are studies indicating that only 13% of firms reported achieving their annual profit objectives (Cooper, 2019; Guarraia, 2008). Researchers have found numerous critical failure factors associated with Six Sigma project failures but there is little research as to whether the underlying causes were related to the accuracy of cost estimate inputs required for manufacturing a product (Antony, Lizarelli, & Machado Fernandes, 2020). There is also an abundance of research studies that discuss critical success factors that support the increased likelihood of product design success so it is reasonable to assume that product design projects that failed may have neglected to implement these factors. Using a two-phase explanatory mixed-methods design that began with a nominal quantitative survey that included 177 Six Sigma practitioners responding to 26 questions. This phase was conducted to verify and validate the proposed research questions. Based on the analysis of the survey results a set of explanatory questions was developed for a qualitative semi-structured interview study that included nine subject matter experts recruited from the field of cost engineering (Creswell, 2015). Using thematic analysis, the responses from the interviews were then coded and categorized. After multiple iterations of analysis themes emerged allowing the researcher to develop a conclusion about the research question (V. Braun & V. Clarke, 2021). The results of this study indicate that the four themes, if implemented properly, can improve the failure rates for Six Sigma projects caused by cost related issues.

The research investigated the adoption of innovation and technologies in the higher education sector in Saudi Arabia. The research focused on studying the individual characteristics of managers and employees of private and public universities. Additionally, the research studied the factors that influenced the diffusion of innovation and the degree level of adopting innovations at the organizations. The invention that was selected to be evaluated for its adoption was Balanced Scorecard (BSC) managerial innovation. The study sample was collected from decision-makers of six public and private universities in Saudi Arabia. These decision-makers involved both formal management and faculty members. The independent variables consist of the perceptions of an invention and the individual factors of prospective adopters. The intention of adoption of innovation is the dependent variable. The research was measuring the variables by using 33 multipoint questionnaires. The research found that the intention of the adoption is affected only by Relative Advantage, Result of Demonstration, Image, Avoidance, and Subjective Norms. However, it was noticed that individual differences variables have no relationship with the intent to adopt the innovation. On the other hand, the individuals' differences factor which is Management Level has a positive relationship with Relative Advantage, Compatibility, Ease of Use, Result of Demonstration, Image, Avoidance, Perceived Voluntariness, and Subject Norms.